FastGPT
clearml
FastGPT | clearml | |
---|---|---|
3 | 20 | |
13,425 | 5,295 | |
13.8% | 2.4% | |
9.7 | 7.7 | |
2 days ago | 3 days ago | |
TypeScript | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
FastGPT
- FLaNK Stack Weekly 12 February 2024
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🌌 5 Open-Source GPT Wrappers to Boost Your AI Experience 🎁
FastGPT is a knowledge-based QA system built on the LLM, offers out-of-the-box data processing and model invocation capabilities, and allows for workflow orchestration. You can use FastGPT to build your own AI knowledge base.
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Accelerate data-driven growth with Google Cloud and Fivetran
!ghbot https://github.com/labring/FastGPT
clearml
- FLaNK Stack Weekly 12 February 2024
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clearml VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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cascade alternatives - clearml and MLflow
3 projects | 1 Nov 2023
- Is there any workflow orchestrator that is Hydra friendly ?
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Show HN: Open-source infra for data scientists
It looks like Magniv is targeting Python in general. This is similar to ClearML. What are the differentiating points to Magniv compared to similar products?
It seems like the product also integrates with SCM systems. Are you using gitea and then containers to push code and data to execution like CodeOcean?
https://github.com/allegroai/clearml
https://codeocean.com/
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[D] Drop your best open source Deep learning related Project
Hi there. ClearML is our open-source solution which is part of the PyTorch ecosystem. We would really appreciate it if you read our README and starred us if you like what you see!
- Start with powerful experiment management and scale into full MLOps with only 2 lines of code.
- Everything you need to log, share, and version experiments, orchestrate pipelines, and scale within one open-source MLOps solution.
- Start with powerful experiment management and scale into full MLOps with only 2 lines of code
What are some alternatives?
AI-Employe - Create browser automation as if you were teaching a human using GPT-4 Vision.
MLflow - Open source platform for the machine learning lifecycle
neural-fortran - A parallel framework for deep learning
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
botpress - The open-source hub to build & deploy GPT/LLM Agents ⚡️
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
Awesome-RAG
kedro-great - The easiest way to integrate Kedro and Great Expectations
llm.report - 📊 llm.report is an open-source logging and analytics platform for OpenAI: Log your ChatGPT API requests, analyze costs, and improve your prompts.
streamlit - Streamlit — A faster way to build and share data apps.
E2B - Secure cloud runtime for AI apps & AI agents. Fully open-source.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️